Multi-scale causality and extreme tail inter-dependence among housing prices
Sang Hoon Kang,
Gazi Uddin (),
Ali Ahmed and
Seong-Min Yoon ()
Economic Modelling, 2018, vol. 70, issue C, 301-309
This study explores multi-scale causality and extreme tail dependence structures among housing prices in four cities: Seoul, Hong Kong, Tokyo, and New York. We apply two different and unique approaches in our analysis of monthly housing price data: (i) the frequency domain Granger casualty test and (ii) the non-parametric copula test. Employing the frequency domain casualty test, we find both bi-directional and uni-directional causalities at different frequency bands. Additionally, the nonlinear copula estimates indicate asymmetric tail dependence for housing price pairs in all four cities. Finally, the Hong Kong housing market has a greater effect on the Seoul and Tokyo housing markets than does the New York housing market.
Keywords: Housing prices; Inter-dependence; Multi-scale causality; Non-parametric copula test; Tail distribution (search for similar items in EconPapers)
JEL-codes: C14 C46 R31 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:70:y:2018:i:c:p:301-309
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().